AI can identify patients at risk of serious arrhythmia, prevent sudden death

Artificial intelligence now predicts deadly heart arrhythmias weeks before they strike, analyzing subtle signals in electrocardiograms with 70% accuracy. Developed by Paris and Harvard researchers, this neural network screened millions of heartbeat recordings from six countries to identify high-risk patterns. The breakthrough could integrate with hospital monitors and even smartwatches, offering real-time life-saving alerts. With sudden cardiac deaths claiming 5 million lives annually, this AI tool marks a major leap in preventive cardiology.

"By analysing their electrical signal for 24 hours, we can identify subjects likely to develop serious arrhythmia within two weeks." — Dr. Laurent Fiorina

AI can identify patients at risk of serious arrhythmia, prevent sudden death

London, March 30: Artificial intelligence (AI) can help scientists identify patients at risk of a serious arrhythmia that is capable of triggering cardiac arrest and sudden death.

Key Points

1 AI neural network analyzes 240K electrocardiograms for arrhythmia signals

2 Detects high-risk patients with 70% accuracy

3 Could integrate with smartwatches for real-time monitoring

4 Targets 5M annual sudden cardiac deaths globally

As part of a new study to be published in European Heart Journal, a network of artificial neurons imitating the human brain was developed by researchers from Inserm, Paris Cite University and the Paris public hospitals group (AP-HP), in collaboration with their colleagues in the US.

During the analysis of data from over 240 000 ambulatory electrocardiograms, this algorithm identified patients at risk of a serious arrhythmia that was capable of triggering cardiac arrest within the following 2 weeks in over 70 per cent of cases.

Each year, sudden cardiac death is responsible for over 5 million deaths worldwide.

AI could help to improve the anticipation of arrhythmias – unexplained heart rhythm disorders which, if severe, can cause fatal cardiac arrest – according to the new study.

As part of this study, a network of artificial neurons was developed by a team of engineers from the company Cardiologs (Philips group) in collaboration with the universities of Paris Cite and Harvard.

What this algorithm does is imitate the functions of the human brain in order to improve the prevention of cardiac sudden death.

The researchers analysed several million hours of heartbeats thanks to data from 240 000 ambulatory electrocardiograms collected in six countries (USA, France, UK, South Africa, India and Czechia).

Thanks to artificial intelligence, the researchers were able to identify new weak signals that herald the risk of arrhythmia. They were particularly interested in the time needed to electrically stimulate and relax the heart ventricles during a complete cycle of cardiac contraction and relaxation.

"By analysing their electrical signal for 24 hours, we realised that we could identify the subjects susceptible of developing a serious heart arrhythmia within the next two weeks. If left untreated, this type of arrhythmia can progress towards a fatal cardiac arrest", explained Dr Laurent Fiorina, researcher at the Paris Cardiovascular Research Centre (PARCC) (Inserm/Paris Cite University).

While the artificial neural network is still in the evaluation phase, it showed itself in this study to be capable of detecting at-risk patients in 70 per cent of cases, and no-risk patients in 99.9 per cent of cases.

In the future, this algorithm could be used to monitor at-risk patients in hospital. If its performances are refined, it could also be used in devices such as ambulatory Holters that measure blood pressure to reveal hypertension risks. It could even be used in smartwatches.

The researchers now aim to conduct prospective clinical studies to test the efficacy of this model under real-world conditions.

https://www.newkerala.com/news/o/ai-identify-patients-risk-serious-arrhythmia-prevent-sudden-death-546